How AI Can Support RPL

How can we use AI constructively in the RPL process without compromising the integrity of our assessments?

Because the truth is, not all use of AI is unethical or deceptive.
When it's used transparently and responsibly, AI can be a powerful enabler.
It can improve accessibility, reduce admin time, and even help candidates express their skills more clearly.

How AI Can Support RPL

Let's start with what appropriate use might look like in RPL.

Imagine a candidate who's been in the workforce for 20 years.
They're applying for a leadership qualification through RPL, but they've never written a formal portfolio.
They know what they've done but struggle to present it clearly on paper.

They might use a tool like ChatGPT to:

• Create a draft summary of their work history based on bullet points they've written

• Rephrase their project descriptions in more professional language

• Or generate a checklist to help them match their evidence to each unit

So, how do we set boundaries?

Here are a few principles that we follow at KnowledgeAccess—and I think they're helpful for the sector more broadly.

First, the use of AI should always be disclosed. If a candidate has used AI to draft part of their portfolio or a self-reflection, this should be clearly stated to the assessor. We're not trying to punish transparency, we're trying to make sound judgments based on the full context.

Second, assessors still need to verify authenticity. This might involve asking candidates to discuss their work, verifying consistency across documents, or verifying third-party endorsements against actual project outcomes or results.

Third, AI should never replace an assessor's judgment. It's a support tool, not a decision-maker. That's true whether you're the candidate or the assessor. When used effectively, there are some real benefits.

AI can:

• Reduce the administrative load on both assessors and candidates

• Improve the clarity of communication, especially for people who struggle with formal writing

• Support candidates from non-English-speaking or neurodiverse backgrounds to structure their thoughts

• Help visualise complex timelines or project contributions in a more straightforward way

  
  

However, we must also be cautious.

RPL is based on the Rules of Evidence, which encompass the principles of authenticity, validity, sufficiency, and currency of evidence. It's also governed by the Principles of Assessment, which include fairness, flexibility, validity, and reliability. No matter how helpful the technology, it can't override those foundations.

So here's the balance we aim for:

Utilise AI to support the process, but not to create the product. Use it to clarify, not to invent. And always keep the human element at the heart of assessment. Ultimately, it's the assessor who determines competence. And it's real-world skills, not synthetic ones, that qualifications should reflect.